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Dynamic Model Checking with Property Driven Pruning to Detect Race Conditions

机译:使用属性驱动的修剪进行动态模型检查以检测竞争条件

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We present a new property driven pruning algorithm in dynamic model checking to efficiently detect race conditions in multithreaded programs. The main idea is to use a lockset based analysis of observed executions to help prune the search space to be explored by the dynamic search. We assume that a stateless search algorithm is used to systematically execute the program in a depth-first search order. If our conservative lockset analysis shows that a search subspace is race-free, it can be pruned away by avoiding backtracks to certain states in the depth-first search. The new dynamic race detection algorithm is both sound and complete (as precise as the dynamic partial order reduction algorithm by Flanagan and Godefroid). The algorithm is also more efficient in practice, allowing it to scale much better to real-world multithreaded C programs.
机译:我们在动态模型检查中提出了一种新的属性驱动的修剪算法,以有效地检测多线程程序中的竞争条件。主要思想是对观察到的执行情况使用基于锁集的分析,以帮助减少动态搜索要探索的搜索空间。我们假设使用无状态搜索算法以深度优先搜索顺序系统地执行程序。如果我们保守的锁集分析显示搜索子空间没有竞争,则可以通过在深度优先搜索中避免回溯到某些状态来删除它。新的动态种族检测算法既完善又完善(与Flanagan和Godefroid提出的动态局部降阶算法一样精确)。该算法在实践中也更加高效,可以更好地扩展到实际的多线程C程序。

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